Robust recognition using eigenimages
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local distance preservation in the GP-LVM through back constraints
ICML '06 Proceedings of the 23rd international conference on Machine learning
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Invariant Object Recognition Robot Vision System for Assembly
CERMA '06 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference - Volume 01
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
The Journal of Machine Learning Research
A machine vision quality control system for industrial acrylic fibre production
EURASIP Journal on Applied Signal Processing
Gaussian Process Dynamical Models for Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking and recognizing actions of multiple hockey players using the boosted particle filter
Image and Vision Computing
Equivalent key frames selection based on iso-content principles
IEEE Transactions on Circuits and Systems for Video Technology
Machine Vision System for Flatness Control Feedback
ICMV '09 Proceedings of the 2009 Second International Conference on Machine Vision
Multimedia Tools and Applications
Tools for semi-automatic monitoring of industrial workflows
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Robust and fast collaborative tracking with two stage sparse optimization
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Automatic workflow monitoring in industrial environments
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Tracking video objects with feature points based particle filtering
Multimedia Tools and Applications
Embedding Motion in Model-Based Stochastic Tracking
IEEE Transactions on Image Processing
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Camera based supervision is a critical part of event detection and analysis applications. However, visual tracking still remains one of the biggest challenges in the area of computer vision, although it has been extensively discussed during in the previous years. In this paper we propose a robust tracking approach based on object flow, which is a motion model for estimating both the displacement and the direction of an object of interest. In addition, an observation model that utilizes a generative prior is adopted to tackle the pitfalls that derive from the appearance changes of the object under study. The efficiency of our technique is demonstrated using sequences captured in a complex industrial environment. The experimental results show that the proposed algorithm is sound, yielding improved performance in comparison with other tracking approaches.